Knife River, MN
Knife River, MN's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Knife River at the 29th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 223 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Knife River at the 26th percentile, close to its 29th-percentile risk score.
What "at risk" means for the buildings here
57.4% of Knife River's 223 buildings sit in USFS's Direct exposure zone, roughly 128 structures close enough to burnable vegetation for flame contact, not just embers — 37.7% fall in the Indirect, ember-only zone and 4.9% are Minimal.
How Knife River compares
There's little gap between Knife River's 29th national percentile and its 36th percentile inside Minnesota, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Knife River ranks 22,253 for wildfire risk (1 is highest) and 24,016 by building count (1 is largest). Within Minnesota alone, it ranks 589 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
What this risk score means for insurance
At the 29th national percentile, Knife River rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Knife River
Because Direct exposure dominates in Knife River (57.4%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Knife River's figures come from
Every one of the two percentiles behind Knife River's 22,253-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Knife River's dominant direct exposure actually means, with real examples from across the dataset.